Enhanced Q Estimation by Iterative Spectral Ratio Method for High Resolution Seismic Reflection Image

Quality factor estimation is an important step in describing rock properties. Also, Q is the major parameter in the application of inverse Q filtering to increase resolution on a deterministic way. Stacked seismic reflection data are often used as input for quality factor estimation because of their high signal to noise ratio. Our simple modelling shows, as expected, that the main parameters (maximum offset, Q factor, layer depth, velocity) affecting the attenuation of the seismic waves along their ray-path significantly distort the attenuation properties of stacked traces because travel time differences due to offset variations are neglected. We propose a method where stacked reflection data is fed into the analysis to maintain the required high signal to noise ratio, while a partial inverse Q filtering (amplitude only) is applied before stacking to compensate for attenuation differences of CMP gather traces due to their offset differences. After a few steps a converging iterative process gives a more accurate Q factor estimation compared to the original method without iteration and offset difference compensation by partial inverse Q filtering.